PROXIMAL: Prediction of Xenobiotic Metabolism
PROXIMAL is a software tool for predicting novel metabolic outcomes for any given enzyme-molecule interaction. Using known reaction pairs from KEGG, PROXIMAL constructs generic transformation patterns (operators), applicable to any molecule with sufficient local structural similarity. The tool then applies those operators to the query molecule, predicting its possible derivative metabolites. This approach is useful in many different applications: from predicting the products of xenobiotic metabolism, to uncovering unanticipated interactions due to enzyme promiscuity.
Query
Enter the enzyme commission number and query molecule to predict possible products, or choose an example from below.
Substrate ()
Molecule drawings are interactive. Hover to zoom in, zoom out, or download the molecule. Drag to view more of the structure.
Products ( total)
Publications
We hope you found this tool useful. If you use PROXIMAL, please cite the following paper:
- Mona Yousofshahi, Sara Manteiga, Charmian Wu, Kyongbum Lee, and Soha Hassoun. “PROXIMAL: a method for Prediction of Xenobiotic Metabolism.” BMC Systems Biology (2015) 9:94. DOI 10.1186/s12918-015-0241-4.
Since its debut, PROXIMAL has been featured in a number of other publications, including:
- Sara A. Amin, Elizabeth Chavez, Vladimir Porokhin, Nikhil U. Nair, and Soha Hassoun. “Towards creating an extended metabolic model (EMM) for E. coli using enzyme promiscuity prediction and metabolomics data.” Microbial Cell Factories 18, 109 (2019). DOI 10.1186/s12934-019-1156-3.
- Neda Hassanpour, Nicholas Alden, Rani Menon, Arul Jayaraman, Kyonbum Lee, and Soha Hassoun. “Biological Filtering and Substrate Promiscuity Prediction for Annotating Untargeted Metabolomics.” bioRxiv 558973, Mar 4, 2019. doi: DOI 10.1101/558973.
Contact
If you have any suggestions or comments regarding this tool, don't hesitate to reach out. Your feedback will be much appreciated!
Soha Hassoun
Department of Computer Science,
Department of Chemical & Biological Engineering,
Department of Electrical & Computer Engineering
Tufts University
617-627-5177
soha (at) cs.tufts.edu
http://www.cs.tufts.edu/~soha/
420 Joyce Cummings Center
177 College Ave
Medford, MA 02155